International Journal of Modern Nonlinear Theory and Application, 2014, 3, 53-65 Published Online July 2014 in SciRes. http://www.scirp.org/journal/ijmnta http://dx.doi.org/10.4236/ijmnta.2014.33008 How to cite this paper: Mahjoub Essefi, R., Souissi, M. and Abdallah, H.H. (2014) Maximum Power Point Tracking Control Using Neural Networks for Stand-Alone Photovoltaic Systems. International Journal of Modern Nonlinear Theory and Ap- plication, 3, 53-65. http://dx.doi.org/10.4236/ijmnta.2014.33008 Maximum Power Point Tracking Control Using Neural Networks for Stand-Alone Photovoltaic Systems Rihab Mahjoub Essefi, Mansour Souissi, Hsan Hadj Abdallah Control and Energy Management Laboratory, National School of Engineering of Sfax, Sfax, Tunisia Email: rihab.mahjoub@yahoo.fr Received 18 May 2014; revised 25 June 2014; accepted 2 July 2014 Copyright © 2014 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/ Abstract The employment of maximum power point tracking techniques in the photovoltaic power systems is well known and even of immense importance. There are various techniques to track the maxi- mum power point reported in several literatures. In such context, there is an increasing interest in developing a more appropriate and effective maximum power point tracking control methodology to ensure that the photovoltaic arrays guarantee as much of their available output power as possi- ble to the load for any temperature and solar radiation levels. In this paper, theoretical details of the work, carried out to develop and implement a maximum power point tracking controller using neural networks for a stand-alone photovoltaic system, are presented. Attention has been also paid to the command of the power converter to achieve maximum power point tracking. Simula- tions results, using Matlab/Simulink software, presented for this approach under rapid variation of insolation and temperature conditions, confirm the effectiveness of the proposed method both in terms of efficiency and fast response time. Negligible oscillations around the maximum power point and easy implementation are the main advantages of the proposed maximum power point tracking (MPPT) control method. Keywords Maximum Power Point Tracking (MPPT), Photovoltaic (PV) System, Neural Network, Buck Converter 1. Introduction In the last few decades, harnessing solar energy found its high usefulness as a way to solve the problems of the